What happens when the most capable AI lives in the cloud, but the work you want it to do is too private, expensive, or repetitive to send there every time?

Dr. Olena Zhu, Head of AI Solutions & Ecosystem for Intel’s Client Computing Group, joins Corey Noles and Grant Harvey to explain Intel’s vision for hybrid AI: systems that route each task to the right place, whether that is a local model on a PC, a larger model on an edge server, or a frontier model in the cloud.

The conversation explores why cloud-only AI may be difficult to scale, how an orchestration layer decides where work should run, and how Intel’s new SuperClaw beta combines local and remote intelligence. Dr. Zhu also explains how hybrid agents could conduct deep research without exposing confidential data, why routing and auditability matter when agents fail, and why the next wave of useful AI may come from specialized agents built for specific jobs.

Listen for a practical look at the tradeoffs among capability, privacy, cost, reliability, and control, and what it could mean when powerful AI agents begin running partly on the computers we already own.

Try Intel SuperClaw: https://aibuilder.intel.com/#/superclaw

Intel AI Builder: https://aibuilder.intel.com/

Intel SuperClaw GitHub: https://github.com/intel/intel-ai-builder/tree/main/superclaw

Intel’s SuperClaw overview: https://newsroom.intel.com/opinion/solving-the-agentic-ai-trilemma-cost-scale-and-data-security

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